This invention pertains to process controllers and is more particularly concerned with process controllers providing adaptive gain closed loop feedback control.
A conventional process controller is a linear device whose job is to control a process which is usually non-linear. However, if the range over which control is exercised is usually so narrow that for all practical purposes the process can be considered linear in that range, the controller can perform successfully. When the range of control is so wide that the non-linear nature of the process is strongly manifested, the ordinary controller is not very effective. Such loops are usually run in the manual mode.
Many industrial process control plants with dozens, even hundreds of conventional PI or PID process control loops, have many loops operating in the manual mode. In fact, anywhere from 25 to 50 percent of industrial "loops" are open loops in which the output is set by the operator. These loops are the so-called "problem" loops, where the operators are more confident in their own abilities to meet any emergencies than they are in the controller's.
An example of a "problem" loop is the control of the level of a liquid in a spherical tank. While control could be a readily accomplished at the half-full point, where almost-linear conditions prevail, the problem is entirely different at near-full or near-empty set points. At these points, level changes so fast and nonlinearly that very high controller gains are needed to keep the level at the set-point. High gains, however, would result in an unstable system that oscillates; too low a gain can result in tank overflow or an empty tank. To avoid this type of problem, more often than not, control is performed manually.
Consider a "well-behaved" linear system or a process under PID control. If the system is linear than the gain for best response is the same at any setpoint. Such a system handles small disturbances around the setpoint without any problem. Suppose now, that a very large disturbance, such as a drastic setpoint change or a large change in process load, occurs. Because the system gain is usually low, it may take a long time for the system controller to catch up with the error. Thus, a "normally tuned" PID controller can have problems following large relatively fast disturbances in the system it is controlling.
Consider another situation in which the system or the process controlled by a PID controller is nonlinear. A linear controller can do an effective conrol job only if the region of control is so narrow that for all practical purposes the nonlinearity can be neglected. If the setpoint is changed to another setting (assume it is done slowly so the controller can follow the change) the controller will have to be retuned to accommodate the non-linear system's new "gain" characteristics. The gain at the original point will not, as a rule, be the optimum gain setting for the new operating point.
In both cases just described the problems could be avoided, or at least the performance markedly improved, if the controller changed its gain automatically to adapt itself to the new operating conditions. A PID controller having fixed gain cannot, by itself, adapt its behavior to signal or process changes as just described. The problem of constant gain was first recognized back in the late 40's by W. I. Caldwell of Taylor. The fixed gain controller does not have the ability to change gain to compensate for a non-linear process and will provide optimum control at only one point on the variables range. At all other points on the range the controllers gain will be too high or too low.
The adaptive gain controller has been gradually accepted by industry because of its ability to change its overall gain in response to a variable or group of variables, so as to maintain a constant or nearly constant loop gain.
A number of patents relating to adaptive gain closed loop feedback control have issued. These patents describe systems which the applicant believes fall into eight conceptual categories. The general approach taken in a category is similar, however specifics are quite different.
I. Magnitude Based Controller Gain
This concept uses the steady state magnitude of one or more variables to predict the required controller gain. For example, the controller gain could be adjusted by error; as the error increases, so does the gain.
The present invention falls under this broad category, but is readily distinguishable over the prior art by a number of novel features.
The following is a partial listing of previous patents in this category.
______________________________________ Patent Number Description ______________________________________ 3,708,754 Two fixed gains with switch- ing determined by Controller Output. 3,731,178 Gain determined by Deviation 2,743,710 Gain determined by Remote Analog signal. 3,569,681 Gain based on Deviation. Has zone of linear control. 3,552,428 Gain based on the Process Variable. 3,906,196 Gain based on Deviation with maximum gain limit. 3,542,048 Gain based on Deviation, a Fluidic Device for a Hydro- foil application. ______________________________________
Other categories will now be briefly described.
II. Transient Based Controller Gain
This concept depends on using both magnitude and time dependent information to predict the controller gain; Reset and Pre-Act functions remain manually adjusted.
The presence of specific frequencies is typically used to detect cycling. Another common idea is to base gain on the deviation of a specific variable.
III. Magnitude Based Controller Responses
This concept uses the steady state magnitude of one or more variables to predict the values of both gain and the dynamic controller responses. For example, Gain, Reset and Pre-Act may all be changes as a function of external signals.
IV. Transient Based Controller Responses
This concept uses both magnitude and time dependent information to adjust both the gain and dynamic controller responses. Depending on how accurate the prediction can be made, this concept could approach the self tuning controller in performance. For example, long sustained offsets might increase reset while oscillation would reduce gain.
V. Induced Disturbance Based Controller Responses
The concept here is to directly measure the process gain and dynamic and set controller responses so that the loop gain and stability remains constant. The method used to measure process characteristics is to induce a disturbance and measure what happens to that specific disturbance.
VI. Process Characteristics Based Controller Responses
This concept measures process gain and dynamics without making additional disturbances. It then re-adjusts controller parameters to keep performance consistent.
VII. Non-linear Gain Elements
This category covers patents, while they are not negative feedback controllers, can be placed into a traditional feedback loop to produce a form of adaptive control.